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Backpropagation: The Intuition

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The intuition of backpropagation: the error flows backward through the network.

Backpropagation shares out the blame for the error among all the weights of a neural network. It propagates an error signal backwards layer by layer, multiplying by the local derivatives, and so obtains the gradient of every weight in a single pass. That idea, published in 1986, is what makes training deep networks possible.

Video transcript
  1. 0:01 First, the forward pass:
  2. 0:03 the input flows through the network to the output.
  3. 0:06 Then the error travels backward, and the chain rule gives each weight its share,
  4. 0:10 layer by layer.

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